How do I import "SQL agent with memory" into n8n?

Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.

Which integrations does "SQL agent with memory" use?

It uses: memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat. The flow diagram above shows how each service connects across the 13 nodes. Filter OpenRuna by integration to find related workflows and tools.

Can I import a sanitized export without credentials?

Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own memoryBufferWindow and lmChatOpenAi credentials in n8n after import.

What trigger type does "SQL agent with memory" use?

Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.

Is "SQL agent with memory" free to use?

OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat.

← Workflows

SQL agent with memory

13 nodes · memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile

Engine: n8n
Nodes: 13
Trigger: scheduled/triggered
Source file: 1294_Compression_Manual_Automation_Webhook.json

Workflow flow

IntegrationsMemoryBufferWindowLmChatOpenAiManualHTTPCompressionReadWriteFileAgentChat@n8n/n8n-nodes-langchain.memoryBufferWindow@n8n/n8n-nodes-langchain.lmChatOpenAiSet@n8n/n8n-nodes-langchain.agent+1 more

100%

Window Buffer Memory

@n8n/n8n-nodes-langchain.memoryBufferWindow

OpenAI Chat Model

@n8n/n8n-nodes-langchain.lmChatOpenAi

TRIGGER

When clicking "Test workflow"

Manual

TRIGGER

Chat Trigger

@n8n/n8n-nodes-langchain.chat

Get chinook.zip example

HTTP

Load local chinook.db

ReadWriteFile

Extract zip file

Compression

Combine chat input with the binary

Set

Save chinook.db locally

ReadWriteFile

AI Agent

@n8n/n8n-nodes-langchain.agent

10 steps · flows top to bottom, branches left to right

Browse by integration

memoryBufferWindow lmChatOpenAi manual httpRequest compression readWriteFile agent chat

Browse all integrations →

Download n8n JSON Download sanitized JSON Download flow graph

Import into n8n

Download the n8n JSON file (full or sanitized).
In n8n: Workflows → Import from file.
Open each node and reconnect credentials to your accounts.
Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

SQL agent with memory is a free n8n workflow on OpenRuna — 13 nodes connecting memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat. Download the JSON, view the flow diagram, and import it into your n8n instance.

What this workflow does

"SQL agent with memory" is an n8n automation built from 13 nodes spanning memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat. 13 nodes · memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile Execution begins at the scheduled/triggered trigger and flows through the 13 configured nodes. On OpenRuna you get the visual graph, the integration list, and a downloadable JSON ready to import into n8n. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

Use it as a starting template when wiring memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat — adjust node parameters to your accounts and record IDs.
Import "SQL agent with memory" into n8n, reconnect credentials for memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat, and run the same automation in your own workspace.
Share it with your team as a documented reference for scheduled/triggered automations in the memoryBufferWindow stack.
Study how data moves from memoryBufferWindow to lmChatOpenAi before building your own variant.

Example output

Imported into n8n, "SQL agent with memory" exposes 13 configured nodes. Trigger type: scheduled/triggered. Integrations: memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat. Reconnect the memoryBufferWindow credential first, then walk the remaining nodes top to bottom. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Paste the exported JSON for "SQL agent with memory" into Claude and ask it to explain each of the 13 nodes. Claude is good at suggesting credential mappings for memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat, plus error-handling and idempotency improvements before you run it in production.

ChatGPT

Have ChatGPT generate a checklist for adapting "SQL agent with memory" to your accounts — which memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat credentials to create and which node parameters to change first.

Cursor

Open the downloaded JSON in Cursor and use Agent mode to refactor hard-coded URLs into env vars, or to generate tests for any Code nodes. Keep the OpenRuna flow diagram open so you do not break connection order across the 13 nodes.

Frequently asked questions

How do I import "SQL agent with memory" into n8n?: Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "SQL agent with memory" use?: It uses: memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat. The flow diagram above shows how each service connects across the 13 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?: Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own memoryBufferWindow and lmChatOpenAi credentials in n8n after import.
What trigger type does "SQL agent with memory" use?: Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "SQL agent with memory" free to use?: OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for memoryBufferWindow, lmChatOpenAi, manual, httpRequest, compression, readWriteFile, agent, chat.